generatorLossesArray.append(0) discriminatorLossesAveragesArray.append( sum(discriminatorLossesArray) / len(discriminatorLossesArray)) generatorLossesAveragesArray.append( sum(generatorLossesArray) / len(generatorLossesArray)) if (epoch % epochsPerPrint == 0): save(generator.state_dict(), './generator.pth') save(discriminator.state_dict(), './discriminator.pth') print("Epoch: ", epoch) plotter.plotImage(generatedImage) plotter.plotImage(image) plotter.multiGraph([ discriminatorLossesAveragesArray, generatorLossesAveragesArray ], ['r', 'w'], epochsPerPrint) else: noise = noiseGenerator.generate(batchSize, channels, (noiseHeight, noiseWidth)) generatedImage = generator(noise) plotter.plotImage(generatedImage) #%% if (training_mode): save(generator.state_dict(), './generator.pth') save(discriminator.state_dict(), './discriminator.pth')